Remove Experimentation Remove ROI Remove Testing
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88% of AI pilots fail to reach production — but that’s not all on IT

CIO Business Intelligence

The proof of concept (POC) has become a key facet of CIOs AI strategies, providing a low-stakes way to test AI use cases without full commitment. Companies pilot-to-production rates can vary based on how each enterprise calculates ROI especially if they have differing risk appetites around AI. Its going to vary dramatically.

ROI 127
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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. What breaks your app in production isnt always what you tested for in dev! The way out?

Testing 174
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6 keys to genAI success in 2025

CIO Business Intelligence

While genAI has been a hot topic for the past couple of years, organizations have largely focused on experimentation. Its the year organizations will move their AI initiatives into production and aim to achieve a return on investment (ROI). Track ROI and performance. In 2025, thats going to change.

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Companies to shift AI goals in 2025 — with setbacks inevitable, Forrester predicts

CIO Business Intelligence

As they look to operationalize lessons learned through experimentation, they will deliver short-term wins and successfully play the gen AI — and other emerging tech — long game,” Leaver said. Their top predictions include: Most enterprises fixated on AI ROI will scale back their efforts prematurely.

ROI 127
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How to Set AI Goals

O'Reilly on Data

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. They don’t automatically generate revenue and growth, maximize ROI, or keep users engaged and loyal. automated retirement portfolio rebalancing and maximized ROI).

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. It is also important to have a strong test and learn culture to encourage rapid experimentation. What is the most common mistake people make around data?

Analytics 250
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What you need to know about product management for AI

O'Reilly on Data

This has serious implications for software testing, versioning, deployment, and other core development processes. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies. What delivers the greatest ROI?